Could Markov chains be applied to any other data sets for hilarious effect? By using Slatton’s Python implementation of Markov chains plus 300,000 descriptions of public GitHub repositories retrieved from their API, I discovered that statistical randomness can indeed create funny innovation.

You can download a list of 1,000 Markov chain-generated projects here. Here are a few interesting ones:

MaNGOS is a free, Open Source implementation of a tag at relatively random intervals.

A Warhammer 40k simulator to teach myself both OpenGL and Clojure

Perl interface to Git repositories via Ruby.

A windows live messenger network client written in Erlang

Rails plugin which allows to talk anonymously and use tripcodes if you want.

Android LED interface library for various wave propagation techniques.

CatchAPI is a Java API to remove the need for boring project setup.

Adds basic social networking capabilities to your lighting system based on the concept of the Working with Rails

Brute force your OpenERP data integration with flatfiles

Culerity integrates Cucumber and Celerity in order to shutdown the computer.

Parses ANSI color codes and converts them to iphone compatible mp4s using HandBrake

A simple OFX (Open Financial Exchange) parser built on top of WordPress. Rolopress core theme

The code used to get the project descriptions from the GitHub API is available in this GitHub repository, and you can download the ~300k repo descriptions here. [5MB .zip]

If you liked this blog post, I have set up a Patreon to fund my machine learning/deep learning/software/hardware needs for my future crazy yet cool projects, and any monetary contributions to the Patreon are appreciated and will be put to good creative use.